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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="preprocessor">#ifndef CAFFE_UTIL_CUDNN_H_</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="preprocessor">#define CAFFE_UTIL_CUDNN_H_</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="preprocessor">#ifdef USE_CUDNN</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;</div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="preprocessor">#include &lt;cudnn.h&gt;</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;</div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">#include &quot;caffe/common.hpp&quot;</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &quot;caffe/proto/caffe.pb.h&quot;</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#define CUDNN_VERSION_MIN(major, minor, patch) \</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">    (CUDNN_VERSION &gt;= (major * 1000 + minor * 100 + patch))</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;</div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="preprocessor">#define CUDNN_CHECK(condition) \</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="preprocessor">  do { \</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="preprocessor">    cudnnStatus_t status = condition; \</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="preprocessor">    CHECK_EQ(status, CUDNN_STATUS_SUCCESS) &lt;&lt; &quot; &quot;\</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="preprocessor">      &lt;&lt; cudnnGetErrorString(status); \</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="preprocessor">  } while (0)</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* cudnnGetErrorString(cudnnStatus_t status) {</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;  <span class="keywordflow">switch</span> (status) {</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;    <span class="keywordflow">case</span> CUDNN_STATUS_SUCCESS:</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;      <span class="keywordflow">return</span> <span class="stringliteral">&quot;CUDNN_STATUS_SUCCESS&quot;</span>;</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;    <span class="keywordflow">case</span> CUDNN_STATUS_NOT_INITIALIZED:</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;      <span class="keywordflow">return</span> <span class="stringliteral">&quot;CUDNN_STATUS_NOT_INITIALIZED&quot;</span>;</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;    <span class="keywordflow">case</span> CUDNN_STATUS_ALLOC_FAILED:</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;      <span class="keywordflow">return</span> <span class="stringliteral">&quot;CUDNN_STATUS_ALLOC_FAILED&quot;</span>;</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;    <span class="keywordflow">case</span> CUDNN_STATUS_BAD_PARAM:</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;      <span class="keywordflow">return</span> <span class="stringliteral">&quot;CUDNN_STATUS_BAD_PARAM&quot;</span>;</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;    <span class="keywordflow">case</span> CUDNN_STATUS_INTERNAL_ERROR:</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;      <span class="keywordflow">return</span> <span class="stringliteral">&quot;CUDNN_STATUS_INTERNAL_ERROR&quot;</span>;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    <span class="keywordflow">case</span> CUDNN_STATUS_INVALID_VALUE:</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;      <span class="keywordflow">return</span> <span class="stringliteral">&quot;CUDNN_STATUS_INVALID_VALUE&quot;</span>;</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;    <span class="keywordflow">case</span> CUDNN_STATUS_ARCH_MISMATCH:</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;      <span class="keywordflow">return</span> <span class="stringliteral">&quot;CUDNN_STATUS_ARCH_MISMATCH&quot;</span>;</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    <span class="keywordflow">case</span> CUDNN_STATUS_MAPPING_ERROR:</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;      <span class="keywordflow">return</span> <span class="stringliteral">&quot;CUDNN_STATUS_MAPPING_ERROR&quot;</span>;</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    <span class="keywordflow">case</span> CUDNN_STATUS_EXECUTION_FAILED:</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;      <span class="keywordflow">return</span> <span class="stringliteral">&quot;CUDNN_STATUS_EXECUTION_FAILED&quot;</span>;</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    <span class="keywordflow">case</span> CUDNN_STATUS_NOT_SUPPORTED:</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;      <span class="keywordflow">return</span> <span class="stringliteral">&quot;CUDNN_STATUS_NOT_SUPPORTED&quot;</span>;</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;    <span class="keywordflow">case</span> CUDNN_STATUS_LICENSE_ERROR:</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;      <span class="keywordflow">return</span> <span class="stringliteral">&quot;CUDNN_STATUS_LICENSE_ERROR&quot;</span>;</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="preprocessor">#if CUDNN_VERSION_MIN(6, 0, 0)</span></div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;    <span class="keywordflow">case</span> CUDNN_STATUS_RUNTIME_PREREQUISITE_MISSING:</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;      <span class="keywordflow">return</span> <span class="stringliteral">&quot;CUDNN_STATUS_RUNTIME_PREREQUISITE_MISSING&quot;</span>;</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;  }</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;  <span class="keywordflow">return</span> <span class="stringliteral">&quot;Unknown cudnn status&quot;</span>;</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;}</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacecaffe.html">caffe</a> {</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;<span class="keyword">namespace </span>cudnn {</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Dtype&gt; <span class="keyword">class </span>dataType;</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;<span class="keyword">template</span>&lt;&gt; <span class="keyword">class </span>dataType&lt;float&gt;  {</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;  <span class="keyword">static</span> <span class="keyword">const</span> cudnnDataType_t type = CUDNN_DATA_FLOAT;</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">float</span> oneval, zeroval;</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;  <span class="keyword">static</span> <span class="keyword">const</span> <span class="keywordtype">void</span> *one, *zero;</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;};</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;<span class="keyword">template</span>&lt;&gt; <span class="keyword">class </span>dataType&lt;double&gt; {</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;  <span class="keyword">static</span> <span class="keyword">const</span> cudnnDataType_t type = CUDNN_DATA_DOUBLE;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">double</span> oneval, zeroval;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;  <span class="keyword">static</span> <span class="keyword">const</span> <span class="keywordtype">void</span> *one, *zero;</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;};</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Dtype&gt;</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;<span class="keyword">inline</span> <span class="keywordtype">void</span> createTensor4dDesc(cudnnTensorDescriptor_t* desc) {</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;  CUDNN_CHECK(cudnnCreateTensorDescriptor(desc));</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;}</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Dtype&gt;</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;<span class="keyword">inline</span> <span class="keywordtype">void</span> setTensor4dDesc(cudnnTensorDescriptor_t* desc,</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    <span class="keywordtype">int</span> n, <span class="keywordtype">int</span> c, <span class="keywordtype">int</span> h, <span class="keywordtype">int</span> w,</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    <span class="keywordtype">int</span> stride_n, <span class="keywordtype">int</span> stride_c, <span class="keywordtype">int</span> stride_h, <span class="keywordtype">int</span> stride_w) {</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;  CUDNN_CHECK(cudnnSetTensor4dDescriptorEx(*desc, dataType&lt;Dtype&gt;::type,</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;        n, c, h, w, stride_n, stride_c, stride_h, stride_w));</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;}</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Dtype&gt;</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;<span class="keyword">inline</span> <span class="keywordtype">void</span> setTensor4dDesc(cudnnTensorDescriptor_t* desc,</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    <span class="keywordtype">int</span> n, <span class="keywordtype">int</span> c, <span class="keywordtype">int</span> h, <span class="keywordtype">int</span> w) {</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> stride_w = 1;</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> stride_h = w * stride_w;</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> stride_c = h * stride_h;</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> stride_n = c * stride_c;</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;  setTensor4dDesc&lt;Dtype&gt;(desc, n, c, h, w,</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;                         stride_n, stride_c, stride_h, stride_w);</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;}</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Dtype&gt;</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;<span class="keyword">inline</span> <span class="keywordtype">void</span> createFilterDesc(cudnnFilterDescriptor_t* desc,</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    <span class="keywordtype">int</span> n, <span class="keywordtype">int</span> c, <span class="keywordtype">int</span> h, <span class="keywordtype">int</span> w) {</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;  CUDNN_CHECK(cudnnCreateFilterDescriptor(desc));</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;<span class="preprocessor">#if CUDNN_VERSION_MIN(5, 0, 0)</span></div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;  CUDNN_CHECK(cudnnSetFilter4dDescriptor(*desc, dataType&lt;Dtype&gt;::type,</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;      CUDNN_TENSOR_NCHW, n, c, h, w));</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;<span class="preprocessor">#else</span></div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;  CUDNN_CHECK(cudnnSetFilter4dDescriptor_v4(*desc, dataType&lt;Dtype&gt;::type,</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;      CUDNN_TENSOR_NCHW, n, c, h, w));</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;}</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Dtype&gt;</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;<span class="keyword">inline</span> <span class="keywordtype">void</span> createConvolutionDesc(cudnnConvolutionDescriptor_t* conv) {</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;  CUDNN_CHECK(cudnnCreateConvolutionDescriptor(conv));</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;}</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Dtype&gt;</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;<span class="keyword">inline</span> <span class="keywordtype">void</span> setConvolutionDesc(cudnnConvolutionDescriptor_t* conv,</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;    cudnnTensorDescriptor_t bottom, cudnnFilterDescriptor_t filter,</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;    <span class="keywordtype">int</span> pad_h, <span class="keywordtype">int</span> pad_w, <span class="keywordtype">int</span> stride_h, <span class="keywordtype">int</span> stride_w) {</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;<span class="preprocessor">#if CUDNN_VERSION_MIN(6, 0, 0)</span></div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;  CUDNN_CHECK(cudnnSetConvolution2dDescriptor(*conv,</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;      pad_h, pad_w, stride_h, stride_w, 1, 1, CUDNN_CROSS_CORRELATION,</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;      dataType&lt;Dtype&gt;::type));</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;<span class="preprocessor">#else</span></div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    CUDNN_CHECK(cudnnSetConvolution2dDescriptor(*conv,</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;      pad_h, pad_w, stride_h, stride_w, 1, 1, CUDNN_CROSS_CORRELATION));</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;}</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Dtype&gt;</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;<span class="keyword">inline</span> <span class="keywordtype">void</span> createPoolingDesc(cudnnPoolingDescriptor_t* pool_desc,</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    PoolingParameter_PoolMethod poolmethod, cudnnPoolingMode_t* mode,</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    <span class="keywordtype">int</span> h, <span class="keywordtype">int</span> w, <span class="keywordtype">int</span> pad_h, <span class="keywordtype">int</span> pad_w, <span class="keywordtype">int</span> stride_h, <span class="keywordtype">int</span> stride_w) {</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;  <span class="keywordflow">switch</span> (poolmethod) {</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;  <span class="keywordflow">case</span> PoolingParameter_PoolMethod_MAX:</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    *mode = CUDNN_POOLING_MAX;</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    <span class="keywordflow">break</span>;</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;  <span class="keywordflow">case</span> PoolingParameter_PoolMethod_AVE:</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    *mode = CUDNN_POOLING_AVERAGE_COUNT_INCLUDE_PADDING;</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;    <span class="keywordflow">break</span>;</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    LOG(FATAL) &lt;&lt; <span class="stringliteral">&quot;Unknown pooling method.&quot;</span>;</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;  }</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;  CUDNN_CHECK(cudnnCreatePoolingDescriptor(pool_desc));</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;<span class="preprocessor">#if CUDNN_VERSION_MIN(5, 0, 0)</span></div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;  CUDNN_CHECK(cudnnSetPooling2dDescriptor(*pool_desc, *mode,</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;        CUDNN_PROPAGATE_NAN, h, w, pad_h, pad_w, stride_h, stride_w));</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;<span class="preprocessor">#else</span></div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;  CUDNN_CHECK(cudnnSetPooling2dDescriptor_v4(*pool_desc, *mode,</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;        CUDNN_PROPAGATE_NAN, h, w, pad_h, pad_w, stride_h, stride_w));</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;}</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Dtype&gt;</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;<span class="keyword">inline</span> <span class="keywordtype">void</span> createActivationDescriptor(cudnnActivationDescriptor_t* activ_desc,</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    cudnnActivationMode_t mode) {</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;  CUDNN_CHECK(cudnnCreateActivationDescriptor(activ_desc));</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;  CUDNN_CHECK(cudnnSetActivationDescriptor(*activ_desc, mode,</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;                                           CUDNN_PROPAGATE_NAN, Dtype(0)));</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;}</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;}  <span class="comment">// namespace cudnn</span></div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;}  <span class="comment">// namespace caffe</span></div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;<span class="preprocessor">#endif  // USE_CUDNN</span></div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;<span class="preprocessor">#endif  // CAFFE_UTIL_CUDNN_H_</span></div><div class="ttc" id="namespacecaffe_html"><div class="ttname"><a href="namespacecaffe.html">caffe</a></div><div class="ttdoc">A layer factory that allows one to register layers. During runtime, registered layers can be called b...</div><div class="ttdef"><b>Definition:</b> blob.hpp:14</div></div>
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